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Modeling and Simulation of Collective Algorithms on HPC Network Topologies using Structural Simulation Toolkit

Modeling and Simulation of Collective Algorithms on HPC Netw...

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2024 Workshops of the international conference for High Performance computing, networking, Storage and Analysis, SC Workshops 2024

作者： Chenna, Sai P. Steyer, Michael Kumar, Nalini Garzaran, Maria Thierry, Philippe Intel Corporation United States

ISBN: (纸本)9798350355543

In the last decade, DL training has emerged as an HPC-scale workload running on large clusters, the size of the largest supercomputers on the Top500 list. The dominant communication pattern in distributed data-parallel DL training is allreduce which is used to sum the model gradients across processes during backpropagation phase. Various allreduce algorithms have been developed to optimize communication time in DL training. Given the scale of DL workloads, it is crucial to evaluate the scaling efficiency of these algorithms on a variety of system architectures. We have extended the Structural Simulation Toolkit (SST) to simulate allreduce and barrier algorithms - Rabenseifner, ring, and, dissemination algorithms. We performed a design space exploration (DSE) study with three allreduce algorithms and two barrier algorithms running on six system network topologies for various message sizes. We quantified the performance benefits of using allreduce algorithms which preserve locality between communicating processes. In addition, we evaluated the scaling efficiency of centralized and decentralized barrier algorithms. © 2024 IEEE.

关键词： collectives design-space exploration discrete event simulation distributed training interconnect design network simulation performance modeling

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Improving Input-Step Performance

Improving Input-Step Performance

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2024 Workshops of the international conference for High Performance computing, networking, Storage and Analysis, SC Workshops 2024

作者： Adams, Joel C. Calvin University Department of Computer Science Grand RapidsMI United States

ISBN: (纸本)9798350355543

In many "Big Data"problems, the data to be analyzed are stored in files;to solve such problems, an input step reads the data from a file into an array for processing. This input step has traditionally been performed sequentially, causing the time to perform that step to grow linearly with N, the number of values in the file. This paper explores different ways to reduce the time consumed by the input step, including the use of different file formats, as well as parallel I/O via MPI-IO. To make parallel I/O easier for students to use, we have created OO_MPI_IO, a new set of C++ abstractions that hide the complexity of MPI-IO. We also demonstrate how these OO_MPI_IO abstractions can (i) improve the scalability of data-intensive problem solutions, and (ii) provide a means of helping students understand Amdahl's and Gustafson's Laws. © 2024 IEEE.

关键词： Amdahl's Law computing distributed Gustafson's Law I/O input MPI output parallel sequential speedup

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Intelligent Intrusion Detection in Software-Defined networking: A Comparative Study of SVM and ANN Models 18

Intelligent Intrusion Detection in Software-Defined Networki...

引用

18th international conference on Future Networks and Communications (FNC) / 20th international conference on Mobile Systems and Pervasive computing (MobiSPC) / 13th international conference on Sustainable Energy Information Technology (SEIT)

作者： Boukraa, Lamiae Essahraui, Siham El Makkaoui, Khalid Ouahbi, Ibrahim Esbai, Redouane Univ Mohammed Premier Multidisciplinary Fac Nador MASI Lab Oujda Morocco Univ Mohammed Premier Multidisciplinary Fac Nador Oujda Morocco

Software-defined networking (SDN) has emerged as a promising approach for managing network infrastructure through a centralized controller. However, the dynamic nature of SDN makes it susceptible to security threats, including DoS and DDoS attacks. Intrusion detection systems (IDS) based on machine learning (ML) can efficiently detect and mitigate these attacks. This study compares two ML models, namely support vector machines (SVM) and artificial neural networks (ANN), for intelligent intrusion detection in SDN. To assess the performance of the ML models, we utilized the NSL-KDD dataset, with a specific emphasis on DDoS attacks, and compared their accuracy (Acc), precision, recall, and F1-score metrics. The implementation outcomes show that SVM is better than ANN regarding response time and Acc. (c) 2023 The Authors. Published by Elsevier B.V.

关键词： Artificial neural Networks (ANN) distributed denial-of-service (DDoS) Intrusion detection system (IDS) Software-defined networking (SDN) Support vector machines (SVM)

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Leveraging the Compute Power of Two HPC Systems for Higher-Dimensional Grid-Based Simulations with the Widely-distributed Sparse Grid Combination Technique 23

Leveraging the Compute Power of Two HPC Systems for Higher-D...

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2023 international conference for High Performance computing, networking, Storage and Analysis, SC 2023

作者： Pollinger, Theresa Van Craen, Alexander Niethammer, Christoph Breyer, Marcel Pflüger, Dirk Institute for Parallel and Distributed Systems Universität Stuttgart Stuttgart Germany High Performance Computing Center Universität Stuttgart Stuttgart Germany

ISBN: (纸本)9798400701092

Grid-based simulations of hot fusion plasmas are often severely limited by computational and memory resources;the grids live in four- to six-dimensional space and thus suffer the curse of dimensionality. However, high resolutions are required to fully capture the physics of interest. The sparse grid combination technique is a multi-scale method in which many anisotropically coarse resolved grids are used to approximate a fine-scale solution - -and it alleviates the curse of *** paper presents the core concepts of the widely-distributed combination technique, which allows us to use the compute power and memory of more than one HPC system for the same simulation. We apply the sparse grid combination technique to a six-dimensional advection problem serving as a proxy for plasma simulations. The full-grid solution approximated by the combination technique would contain ≈ 5 ZB if computed with conventional grid-based methods. Even the combination technique simulation operates on ≈ 1 × 1011 double-precision degrees of freedom, or 988 GB, plus the supporting sparse grid data structures. We propose a new approach to divide the compute load between the two HPC systems, requiring only 76 GB to be exchanged. Based on this, we have realized the first synchronous combination technique simulation using two HPC systems, in our case the two German Tier-0 supercomputers HAWK and SuperMUC-NG. On two systems, the simulation can be computed at an average overhead of ≈ 35 % (108 s per combination step) for file I/O and transfer. The presented concepts apply to any pair of HPC systems if high-speed data transfer is possible. © 2023 ACM.

关键词： Supercomputers

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distributed Yang Model Dependency Installation Solution 15

Distributed Yang Model Dependency Installation Solution

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15th international conference on computing Communication and networking Technologies, ICCCNT 2024

作者： Bipin, B. Nokia Networks Cns Ece Solutions Bangalore India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370249

Sysrepo is a YANG(Yet another next Generation)-based configuration and operational state data store for Unix/Linux based applications. Applications will be able to use sysrepo to store their configurations, provided by YANG model. Instead of using normal configuration files, sysrepo will ensure data consistency of the data stored in the datastore and enforce data constraints defined by YANG model. YANG is a data modeling language for the definition of data sent over network management protocols such as the NETCONF and RESTCONF. While installing the YANG models into sysrepo, each YANG model follows a set of preconditions. These preconditions can be like, before installing a YANG model a set of specific yangs has to be there in the system. These dependent YANG models can be the ones which users manually have to install or sometimes it could be the ones which are system defined. While installing these, if the dependent ones are not present in sysrepo, then installation process fails. Here in this paper, a new approach is proposed where in the dependent YANG models will be ordered properly and parallel installation will be done which will fasten up the sysrepo and netopeer processes to startup. © 2024 IEEE.

关键词： Protocols Computational modeling Logic gates Data models Next generation networking

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On Scaling Neuronal Network Simulations Using distributed computing

On Scaling Neuronal Network Simulations Using Distributed Co...

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2024 Workshops of the international conference for High Performance computing, networking, Storage and Analysis, SC Workshops 2024

作者： Omelyusik, Vladimir Shehzad, Khawar Banks, Tyler Rao, Praveen Nair, Satish S. University of Missouri United States

ISBN: (纸本)9798350355543

We investigated the computational capabilities of FABRIC, a nationwide research infrastructure with nearly 40 sites, for scaling neuroscience simulations. From the hardware standpoint, single-site characterization showed that FABRIC is a promising alternative to conventional neuroscience setups, particularly due to the availability of powerful graphics processing units (GPUs). While multi-site simulations are affected by network latency, it becomes less critical for larger networks. From the software perspective, we found that in the popular CoreNEURON library, cell distribution strategy (for parallel execution) does not affect the simulation time for biologically realistic networks, while other cases can be addressed with a minimum k-cut graph partitioning algorithm. Overall, scalability experiments revealed that FABRIC can be used to simulate networks of up to twenty-five thousand cells, with the limiting issue being GPU memory. © 2024 IEEE.

关键词： FABRIC GPUs networks neuroscience scalability simulation

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Investigating Novel Approaches to Interactive Communication Media Algorithms for networking Applications

Investigating Novel Approaches to Interactive Communication ...

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2024 international conference on Optimization computing and Wireless Communication, ICOCWC 2024

作者： Haripriya Das, Neeraj Kumar, Prashant Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Teetthanker Mahaveer University College of Engineering Uttar Pradesh Moradabad India

ISBN: (纸本)9798350383348

This paper examines novel techniques for interactive communication media algorithms for networking applications. In latest a long time, there have been substantial traits within the field of statistics communications. As a result, various alternatives for interactive communique media algorithms gift themselves. This paper investigates the usage of various media algorithms for networking packages. Those algorithms consist of peer-to-peer networking, distributed walking, grid computing, and ant colony optimization. A comparative evaluation of these media algorithms is provided via an assessment of the literature and a compilation of to-be-had assets. The overall performance metrics and features of interactive conversation media algorithms are discussed, and their effectiveness and performance are compared. The research also examines the present-day kingdom of interactive media algorithms and their future possibilities. Consequently, a conclusion is drawn regarding the suitability of different algorithms for networked programs. The technical abstract describes the research investigating novel techniques for interactive conversation media algorithms for networking applications. The research aims to provide solutions to expanding allotted communique media algorithms in a dispensed networking device. The specific research focuses on growing advanced algorithms for interactive communication media to aid remote communications on networks. The studies will emphasize numerous robust implementations of the algorithms and the use of mathematical modeling and simulations. The research intends to analyze the proposed algorithms' performance and scalability in numerous networking environments. Moreover, the studies will look at the software of algorithms for numerous Wi-Fi verbal exchange protocols consisting of the IEEE 802.11n general. In the end, the studies may also explore the security factors of the proposed algorithms, with a particular interest in the range of algorithms u

关键词： algorithms Consequently insert optimization styling

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Performance Characterization and Provenance of distributed Task-based Workflows on HPC Platforms

Performance Characterization and Provenance of Distributed T...

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2024 Workshops of the international conference for High Performance computing, networking, Storage and Analysis, SC Workshops 2024

作者： Gueroudji, Amal Phelps, Chase Islam, Tanzima Z. Carns, Philip Snyder, Shane Dorier, Matthieu Ross, Robert B. Pouchard, Line C. Argonne National Laboratory United States Texas State University United States Sandia National Laboratories United States

ISBN: (纸本)9798350355543

Understanding performance and provenance of task-based workflows poses significant challenges, particularly in distributed configurations where resources are shared by multiple applications. Task-based workflow management systems further complicate performance predictability because of their dynamicity that subtly alters task execution order from run to run. In this paper we propose a layered characterization framework for performance and task provenance for *** workflows running on high-performance computing (HPC) platforms. It collects data from jobs, the workflow management system, and the operating system to aid in understanding the performance of these workflows. Our approach encompasses three main contributions: first, an extension of *** to capture high-fidelity task provenance using Mochi data services;second, the adaptation of the established HPC I/O characterization tool Darshan to gather high-fidelity I/O data, thereby enhancing the granularity of our analysis;and third, a framework to combine and process the collected data and provide helpful insights into performance characterization and reproducibility, alongside our lessons learned. © 2024 IEEE.

关键词： Dask High-performance computing (HPC) performance characterization performance reproducibility performance variability provenance task-based workflows

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The QUANT-NET Testbed Development and Preliminary Results 5

The QUANT-NET Testbed Development and Preliminary Results

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2024 international conference on Quantum computing and Engineering

作者： Schon, Damian Umesh, Prathwiraj Cheah, You-Wei Yu, Se-Young Kissel, Ezra Valivarthi, Raju Saglamyurek, Erhan Ramakrishnan, Lavanya Wu, Wenji Sipahigil, Alp Spiropulu, Maria Haffner, Hartmut Monga, Inder Univ Hamburg Hamburg Germany Univ Calif Berkeley Berkeley CA USA CALTECH Pasadena CA USA Lawrence Berkeley Natl Lab Berkeley CA USA

ISBN: (纸本)9798331541378

The U.S. Department of Energy (DOE) is currently supporting Berkeley Lab (LBNL), UC Berkeley (UCB), Caltech, and the University of Innsbruck in constructing a testbed for quantum networking technologies (QUANT-NET). The goal is to establish this network between two sites, LBNL and UCB, connected with an entanglement swapping substrate over similar to 5 km optical fiber and managed by a quantum network protocol stack. On top of this entanglement swapping substrate the research team will implement the most basic building blocks of distributed quantum computing and quantum repeaters by teleporting a controlled-NOT gate between two far trapped-ion quantum computation nodes. This paper presents QUANT-NET, its design, key technologies, and preliminary results. The preliminary results are focused on the QUANT-NET testbed infrastructure control, measurement, and characterization, which includes the implementation of a Hong-Ou-Mandel (HOM) interferometer across the fiber links, and the development and deployment of link polarization drift control in the testbed. These implementations are critical to our next stage research activities.

关键词： quantum network testbed quantum network architecture and protocol stack trapped-ion quantum networking quantum network control

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Real-Time Anomaly Detection Using distributed Tracing in Microservice Cloud Applications 12

Real-Time Anomaly Detection Using Distributed Tracing in Mic...

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12th international conference on Cloud networking (CloudNet)

作者： Raeiszadeh, Mahsa Ebrahimzadeh, Amin Saleem, Ahsan Glitho, Roch H. Eker, Johan Mini, Raquel A. F. Concordia Univ CIISE Montreal PQ Canada Ericsson Res Lund Sweden Univ Western Cape Comp Sci Programme Cape Town South Africa

ISBN: (纸本)9798350313062;9798350313079

distributed tracing plays a vital role in microservice infrastructure, and learning-based trace analysis has been utilized to detect anomalies within such systems. However, existing approaches for learning-based trace-based anomaly detection face certain limitations. Some assume that trace patterns can be learned solely from normal executions, while others depend on anomaly injection to generate labeled traces categorized as normal or anomalous. However, in practical scenarios, anomalies may also happen during the normal execution. Moreover, a wide variety of anomalies may occur in practice, which cannot be captured solely through anomaly injection. To address these issues, we propose a Trace-Driven Anomaly Detection (TDAD) approach based on a Span Causal Graph (SCG) representation, which trains a model using a Graph Neural Network (GNN) and Positive and Unlabeled (PU) learning. This technique allows the model parameters to be optimized by estimating the underlying data distribution. As a result, TDAD can be effectively trained using a small number of labeled anomalous traces along with a relatively large number of unlabeled traces. Our evaluation reveals that TDAD outperforms not only the existing unsupervised trace-based anomaly detection methods by 11.9% in terms of F-1-score but also a supervised learning-based benchmark by 12x in terms of detection time.

关键词： Anomaly Detection distributed Tracing Microservice Positive and Unlabeled Learning

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